prothr

A data frame of 488 liver cirrhosis patients from a randomized clinical trial concerning prednisone
treatment in these patients. The dataset is in long format. The included variables are<dl>
<dt>id</dt>
<dd>Patient identification number</dd><dt>from</dt>
<dd>Starting state</dd><dt>to</dt>
<dd>Receiving state</dd><dt>trans</dt>
<dd>Transition number</dd><dt>Tstart</dt>
<dd>Starting time</dd><dt>Tstop</dt>
<dd>Transition time</dd><dt>status</dt>
<dd>Status variable; 1=transition, 0=censored</dd><dt>treat</dt>
<dd>Treatment; factor with levels "Placebo", "Prednisone"</dd>
</dl>

datasets

The inference in multi-state models is traditionally performed under
a Markov assumption that claims that past and future of the process
are independent given the present state. In this package, we
consider tests of the Markov assumption that are applicable to
general multi-state models. Three approaches using existing
methodology are considered: a simple method based on including
covariates depending on the history in Cox models for the transition
intensities; methods based on measuring the discrepancy of the
non-Markov estimators of the transition probabilities to the
Markov Aalen-Johansen estimators; and, finally, methods that were
developed by considering summaries from families of log-rank
statistics where patients are grouped by the state occupied of the
process at a particular time point (see Soutinho G, Meira-Machado L
(2021) <doi:10.1007/s00180-021-01139-7> and Titman AC, Putter H
(2020) <doi:10.1093/biostatistics/kxaa030>).

Gustavo Soutinho

markovMSM

Methods for Checking the Markov Condition in Multi-State
Survival Data

Luis Meira-Machado

prothr function

Format

Gustavo Soutinho and Luis Meira-Machado.

Author

A data frame of 488 liver cirrhosis patients from a randomized clinical trial concerning prednisone
treatment in these patients. The dataset is in long format. The included variables are<dl>
<dt>id</dt>
<dd>Patient identification number</dd>

<dt>from</dt>
<dd>Starting state</dd>

<dt>to</dt>
<dd>Receiving state</dd>

<dt>trans</dt>
<dd>Transition number</dd>

<dt>Tstart</dt>
<dd>Starting time</dd>

<dt>Tstop</dt>
<dd>Transition time</dd>

<dt>status</dt>
<dd>Status variable; 1=transition, 0=censored</dd>

<dt>treat</dt>
<dd>Treatment; factor with levels "Placebo", "Prednisone"</dd>


</dl>

prothr: Liver cirrhosis data - Abnormal prothrombin levels in liver cirrhosis.

Description

Usage

Arguments

Format

Author

References

Examples